module specification

This module will enable students to understand the Internet of Things (IoT) and Cloud Computing concepts, building blocks, ecosystems, infrastructure, and applications. This will enrich their knowledge and understanding of the core technologies and platforms for IoT and Clouds, that allows digitally enabled devices or objects to collect, gather, and transfer data over a network without involving human-to-human or human-to-machine interaction.
The module will place emphasis on IoT components and delivery models, IoT system architecture, key wireless/mobile/sensor technologies, IoT communication protocols, issues of privacy and trust, cloud platform, and virtualization technologies in the development of IoT cloud infrastructure and applications.
Students will be supported with a series of exercises performed using a powerful network simulation tool, that will cover the range of basic principles to more advanced IoT system design. This will allow students to get real world experience in building IoT system by integrating sensor devices and cloud for creating interconnected solutions to smart cities, homes, and enterprises. Some basic knowledge of Python will be used throughout. By the end of the module, you will get experience in solving real-world problems (IoT and Cloud system implementation) efficiently using simulation modelling.

1. Introduction to IoT – Theory, Evolution, Elements of an IoT Ecosystem, Applications, and Implications.

2. Sensors & Actuators for IoT Systems.

3. Communication Protocols and Networks – Wireless Technologies, Protocol Stacks for the Edge Devices, Wireless Sensor Networks.

4. IoT Networking and Messaging Protocols – CoAP, MQTT, REST, AMQP, WebSocket.

5. Cloud Computing - Architecture: Infrastructure, Virtualisation, Platforms and Software.

6. Cloud Platform and Management for IoT – Application Development and Integration, Hardware Development Boards and Software Platforms for IoT, Issues and Challenges, Security, trust and Privacy Issues.

7. Design a simple IoT system by integrating sensor devices, data processing units, wireless networks, and cloud-based analytics for creating interconnected solutions.

8. IoT Case Studies: Industrial IoT, Business Impact of the IoT/Cloud Computing.

Learning Outcomes LO1 - LO5

Teaching activity will be a combination of formal lectures, supported by tutorial and workshop sessions, and blended learning as follows:

Lecture Materials (1 hour / week): Theoretical background, underpinning principles, and concepts identified in the syllabus will be delivered and discussed during the lectures.

Tutorial/ Workshop (2 hour / week): Complementing lectures by supervised tutorial sessions to gain competency in application of these principles using suitable computational/simulation tool. via Conducting class and group discussions for consolidating understanding of topics introduced in the lecture session.

Blended learning: Contents will be delivered using the University’s VLE and a few other online tools. Assessment and feedback will be provided, to encourage active learning, and to enhance student engagement in the learning process.

All required learning material for the module (lectures/ tutorials/ workshops/ recordings / links etc) will be available to students on University VLE (Weblearn). The module page on VLE will be continuously updated with announcements and need based additional information to ensure appropriate support for students’ learning.

Students will be encouraged to provide reflective commentaries concerning their action plan for personal development on the learning activities and for the tasks that they have carried out to complete the project report, e.g., in the form of a reflective discussion/critical analysis section of their coursework report.
Students will be encouraged to keep logbook for reflective learning and regular feedback.

On successful completion of this module, the student will be able to:

LO1 Understand the core IoT concepts, system components, infrastructure, and applications. Understand the key components that make up an IoT system, including (passive and active) sensors, actuators, physical communications layer, and message protocols. Know the key wireless technologies used in IoT systems, such as WiFi, 6LoWPAN, Bluetooth and ZigBee.

LO2 Evaluate the strengths and weaknesses of different types of cloud-based architectures. Analyse and critically assess the link between IoT, cloud computing, and data analytics.

LO3 Express a critical understanding of how IoT concept fits within the industry (Industry 4.0) and future trends. Appraise the potential of Internet of things (IoT) in an industrial context (also known as Industrial IoT or IIoT) for automating specific tasks, through drawing case studies from the industrial applications of IoT and Cloud Computing.

LO4 Gain real world experience in designing and building a simple IoT system by integrating sensor devices, data processing units, wireless networks and cloud-based analytics for creating interconnected solutions.

LO5 Apply broad skill in writing a report as a tool to communicate the results or findings of the case studies. Gain exposure to the practice of formulating and structuring problems.

Students are assessed by two compulsory assessments [LO1-5].
The first compulsory assessment is the coursework which will consist of two parts: i) lab assignments ii) individual case study. The lab will include set assignments and the deliverable will be documented in a logbook. The logbook will be used to assess student’s continuous engagement with the lab activities, and reflection on practical results. It will enable students to gain real world experience in designing and building simple IoT and cloud-based systems using any network simulator tool, demonstrating their skills for problem-solving and critical evaluation [LO3, LO4].
The individual case study will include an investigation on an agreed student-selected research topic within the IoT and cloud-based system adoption in industrial implementation and the deliverable will be a 1500 words lab report structured in the form of a research paper that will provide students with the opportunity to undertake research in enhancing their knowledge on the potential of IoT and cloud-based systems in an industrial context [LO3, LO5].

The second compulsory assessment is a 2-hour written exam based on material drawn from formal lecture and tutorial content and will test student’s retention, understanding and insight of the theoretical concepts and underlying principles [LO1, LO2, LO4].
Students will receive oral one to one feedback on logbook and usage of technical tools during laboratory sessions. Student may avail formative feedback on the draft submission one week prior to formal submission. Summative feedback on submitted coursework will be provided via VLE (i.e. WebLearn) as per University guidelines.

https://rl.talis.com/3/londonmet/lists/F726EA68-5FB1-0B98-3EEE-E3E88B96D7A0.html

Textbooks:

Core Text:
• Cirani, S., Ferrari, G., Picone, M., & Veltri, L. (2018). Internet of things: architectures, protocols and standards. John Wiley & Sons.
• Raj, P., & Raman, A. C. (2017). The Internet of Things: Enabling technologies, platforms, and use cases. CRC Press.
• Gillam, L., & Antonopoulos, N. (Eds.). (2017). Cloud computing: principles, systems and applications. Springer.
• Iqbal, M.A., Hussain, S., Xing, H. and Imran, M.A., 2020. Enabling the Internet of Things: Fundamentals, Design and Applications. John Wiley & Sons.

Other Texts:
• Holler, J., Tsiatsis, V., Mulligan, C., Avesand, S., Karnouskos, S., & Boyle, D. (2014). From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence. Elsevier.
• Khan, J.Y. and Yuce, M.R. eds., 2019. Internet of Things (IoT): Systems and Applications. CRC Press.
• Buyya, R. and Dastjerdi, A.V. eds., 2016. Internet of Things: Principles and paradigms. Elsevier.
• Rountree, D. and Castrillo, I., 2013. The basics of cloud computing: Understanding the fundamentals of cloud computing in theory and practice. Newnes.
• Tyagi, H. and Kumar, R., 2020. Cloud computing for iot. In Internet of Things (IoT) (pp. 25-41). Springer, Cham.
• McEwen, A., & Cassimally, H. (2013). Designing the internet of things. John Wiley & Sons.
• Ramakrishnan, R. and Gaur, L., 2019. Internet of things: approach and applicability in manufacturing. CRC Press.
• Thera, D., 2020. Internet of Things Simulation Using Cisco Packet Tracer (Doctoral dissertation, Izmir Institute of Technology (Turkey)).
• Finardi, A., 2018. IoT Simulations with Cisco Packet Tracer.
• Iqbal, M.A., Hussain, S., Xing, H. and Imran, M.A., 2021. Packet Tracer and IoT.

Journals:
• IEEE Internet of Things journal, http://ieee-iotj.org/
• Biswas, A.R. and Giaffreda, R., 2014, March. IoT and cloud convergence: Opportunities and challenges. In 2014 IEEE World Forum on Internet of Things (WF-IoT) (pp. 375-376). IEEE.
• Botta, A., De Donato, W., Persico, V. and Pescapé, A., 2016. Integration of cloud computing and internet of things: a survey. Future generation computer systems, 56, pp.684-700.
• Internet of Things, https://www.journals.elsevier.com/internet-of-things
• Alfarsi, G., Jabbar, J., Tawafak, R.M., Malik, S.I., Alsidiri, A. and Alsinani, M., 2019. Using Cisco Packet Tracer to simulate smart home. International Journal of Engineering Research & Technology, 8(12), pp.670-674.
• Almalki, F.A., 2020. Implementation of 5G IoT based smart buildings using VLAN configuration via Cisco packet tracer. International Journal of Electronics Communication and Computer Engineering, 11(4), pp.56-67.

Websites:
• Microsoft’s official Internet of Things (IoT) blog: https://blogs.microsoft.com/iot/
• Amazon Web Services: https://aws.amazon.com/
• IBM official Internet of Things (IoT) blog https://www.ibm.com/blogs/internet-of-things/
• Udemy: https://www.udemy.com/introduction-to-cloud-computing/